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Aggregator-Based Optimization of Community Solar Energy Trading Under Practical Policy Constraints: A Case Study in Thailand

Author

Listed:
  • Sanvayos Siripoke

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Varinvoradee Jaranya

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Chalie Charoenlarpnopparut

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Ruengwit Khwanrit

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Puthisovathat Prum

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Prasertsak Charoen

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

Abstract

This paper presents SEAMS (Solar Energy Aggregator Management System), an optimization-based framework for managing solar energy trading in smart communities under Thailand’s regulatory constraints. A major challenge is the prohibition of residential grid feed-in, which limits the use of conventional peer-to-peer energy models. Additionally, fixed pricing is required to ensure simplicity and trust among users. SEAMS coordinates prosumer and consumer households, a shared battery energy storage system (BESS), and a centralized aggregator (AGG) to minimize total electricity costs while maintaining financial neutrality for the aggregator. A mixed-integer linear programming (MILP) model is developed to jointly optimize PV sizing, BESS capacity, and internal buying price, accounting for Time-of-Use (TOU) tariffs and local policy limitations. Simulation results show that a 6 kW PV system and a 70–75 kWh shared BESS offer optimal performance. A 60:40 prosumer-to-consumer ratio yields the lowest total cost, with up to 49 percent savings compared to grid-only systems. SEAMS demonstrates a scalable and policy-aligned approach to support Thailand’s transition toward decentralized solar energy adoption and improved energy affordability.

Suggested Citation

  • Sanvayos Siripoke & Varinvoradee Jaranya & Chalie Charoenlarpnopparut & Ruengwit Khwanrit & Puthisovathat Prum & Prasertsak Charoen, 2025. "Aggregator-Based Optimization of Community Solar Energy Trading Under Practical Policy Constraints: A Case Study in Thailand," Energies, MDPI, vol. 18(13), pages 1-38, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3231-:d:1683612
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